1. Field of the Invention
The present application is related to providing recommendations of media items of various media types for a media item of a different type.
2. Description of the Background Art
Many websites also provide access to different types media content items (or “media items”, or “items”), such as music, movies, e-books, news articles, user generated content, and so forth. In many case, recommendations are made to other items that are believed to be related (or relevant) to whatever item is currently presented to a user. Many different techniques may be used to determine what related items to display. One technique includes a simple listing of the most popular items available to the website. Another technique includes tagging each item with a descriptive tag that summarizes the content of the item, wherein two items are determined to be related if they have the same tag.
A more robust technique for determining other related items is to measure co-interactions between different media content items of the same type. For example, in order to determine what news articles posted on a website are relevant to each other, user interactions with the website may be monitored to track the website links users visit on a computer (e.g., by clicking with a mouse). The determination includes tracking what news article viewers view before or after viewing a given news article. This technique may be referred to co-click (or co-read or co-view) analysis, as it analyzes what other news articles a viewer clicks on to read in proximity to having clicked on the given news article. Here the co-click analysis is limited to media items of the same type (news articles).
The assumption underlying co-click analysis is that if a viewer clicks through to read some articles but not others, the articles the viewer chose to read are more likely to be related to each other than the articles not read. Aggregated over many viewers, co-click analysis provides a human-usage based view of relatedness between news articles. Co-click analysis may be performed for other content, and be referred to by different names. For example, for web hosted videos this analysis may be referred to as co-watch analysis, and for purchases of goods via internet this analysis may be referred to as co-purchase analysis. Again, each of these analyses requires that the media items are of the same type (e.g., video, purchased goods).
For new media content items that are being posted to the web site for the first time, no co-click statistics regarding the behavior of viewers are available as no user interactions have been recorded yet for the new item. As a consequence, conventional co-click analysis cannot be used to determine what other items are related to the new items. Thus some sites simply do not recommend related items until a sufficient number of user interactions have been obtained for the new item. However, the sooner such a determination is made (i.e., the lower the number of required interactions), the less accurate the determination is likely to be, so these sites typically must wait some period of time in order to accumulate a sufficiently large number of interactions. Not being able to provide recommendations of items related to new items during this period represents a potential loss of business for the website operator. For websites that host time-sensitive media content items, new items are often most viewed when they initially appears on the website. For these types of websites, conventional co-click analysis is unable to provide recommendations for related items when they are needed most.